A method includes determining, by a computing device of a storage network, a pillar width to decode threshold ratio of a dispersed storage error encoding function based on routing path performance information of a set of routing paths with respect to a set of storage units of the storage network. The method further includes dispersed storage error encoding a data object in accordance with the pillar width to decode threshold ratio to produce a plurality of sets of encoded data slices. The method further includes sending the plurality of sets of encoded data slices to the set of storage units via the set of routing paths for storage therein.
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9. The method of claim 8, wherein the modifying the set of routing paths comprises removing a routing path from the set of routing paths to produce an updated set of routing paths.
This invention relates to network routing optimization, specifically improving the efficiency of routing paths in a network. The problem addressed is the need to dynamically adjust routing paths to enhance performance, reduce congestion, or improve reliability in communication networks. The invention provides a method for modifying a set of routing paths by selectively removing one or more paths to produce an updated set of routing paths. This modification is based on network conditions, such as traffic load, latency, or link failures, to optimize routing decisions. The method may involve analyzing the current set of routing paths, evaluating their performance, and determining which paths should be removed to improve overall network efficiency. The updated set of routing paths is then used to guide data transmission, ensuring better resource utilization and minimizing bottlenecks. This approach is particularly useful in large-scale networks where dynamic adjustments are necessary to maintain optimal performance. The invention may be applied in various network environments, including data centers, telecommunication networks, and cloud computing infrastructures, to enhance routing flexibility and adaptability.
10. The method of claim 8, wherein the modifying the set of routing paths comprises adding a new routing path to the set of routing paths to produce an updated set of routing paths.
This invention relates to network routing optimization, specifically methods for dynamically adjusting routing paths to improve network performance. The problem addressed is the need to efficiently modify routing paths in a network to accommodate changing conditions, such as congestion, link failures, or new traffic demands, without disrupting ongoing communications. The method involves analyzing a set of existing routing paths in a network to determine if modifications are necessary. If modifications are required, the method includes adding a new routing path to the existing set to produce an updated set of routing paths. This updated set is then used to route network traffic more effectively. The addition of new paths may be based on factors such as network load, latency, or reliability, ensuring that traffic is routed through the most optimal paths available. The method may also involve evaluating the impact of the new routing path before implementation to ensure it improves network performance. This could include simulating the effect of the new path on traffic flow or verifying that it does not introduce new bottlenecks. The updated set of routing paths is then deployed across the network, allowing routers and switches to use the new configuration for routing decisions. This approach enables dynamic adaptation of network routing to changing conditions, improving efficiency and reliability in data transmission.
19. The computing device of claim 18, wherein the processing module is operable to modify the set of routing paths by removing a routing path from the set of routing paths to produce an updated set of routing paths.
This invention relates to computing devices configured to manage and optimize routing paths in a network. The problem addressed is the need for efficient and adaptive routing path management to improve network performance, reliability, and resource utilization. The computing device includes a processing module that dynamically adjusts routing paths based on network conditions, such as congestion, latency, or link failures. The processing module can modify the set of routing paths by removing one or more paths to produce an updated set of routing paths, ensuring optimal routing decisions. This modification may be based on real-time data, predictive analytics, or predefined rules to enhance network efficiency. The device may also include a monitoring module to track network performance metrics and a storage module to retain routing configurations. The invention aims to provide a flexible and scalable solution for network routing optimization, particularly in environments with dynamic traffic patterns or infrastructure changes. By selectively removing inefficient or redundant paths, the system improves overall network throughput and reduces latency. The technology is applicable to various network types, including data centers, cloud computing environments, and telecommunications networks.
20. The computing device of claim 18, wherein the processing module is operable to modify the set of routing paths by adding a new routing path to the set of routing paths to produce an updated set of routing paths.
This invention relates to computing devices configured to manage routing paths in a network. The problem addressed is the need to dynamically adjust routing paths to optimize network performance, such as improving data transmission efficiency or reducing latency. The computing device includes a processing module that modifies a set of routing paths by adding a new routing path to produce an updated set of routing paths. The processing module may also analyze network conditions, such as traffic load or link quality, to determine when and how to add new routing paths. The updated set of routing paths is then used to route data packets through the network, ensuring more efficient and reliable data transmission. The invention may be applied in various network environments, including data centers, cloud computing systems, and telecommunications networks, where dynamic routing adjustments are critical for maintaining optimal performance. The system may also include a monitoring module to continuously assess network conditions and trigger updates to the routing paths as needed. This approach allows the computing device to adapt to changing network demands, improving overall network reliability and efficiency.
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March 4, 2021
December 13, 2022
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